Lower Extremity Motor System Neuroprostheses

Design and Testing of Stimulation and Myoelectric Recording Modules in an Implanted Distributed Neuroprosthetic System

Implantable motor neuroprostheses can restore functionality to individuals with neurological disabilities by electrically activating paralyzed muscles in coordinated patterns. The typical design of neuroprosthetic systems relies on a single multi-use device, but this limits the number of stimulus and sensor channels that can be practically implemented. To address this limitation, a modular neuroprosthesis, the "Networked Neuroprosthesis" (NNP), was developed. The NNP system is the first fully implanted modular neuroprosthesis that includes implantation of all power, signal processing, biopotential signal recording, and stimulating components. This paper describes the design of stimulation and recording modules, bench testing to verify stimulus outputs and appropriate filtering and recording, and validation that the components function properly while implemented in persons with spinal cord injury. The results of system testing demonstrated that the NNP was functional and capable of generating stimulus pulses and recording myoelectric, temperature, and accelerometer signals. Based on the successful design, manufacturing, and testing of the NNP System, multiple clinical applications are anticipated.

Using Person-Specific Muscle Fatigue Characteristics to Optimally Allocate Control in a Hybrid Exoskeleton - Preliminary Results

Currently controllers that dynamically modulate functional electrical stimulation (FES) and a powered exoskeleton at the same time during standing-up movements are largely unavailable. In this paper, an optimal shared control of FES and a powered exoskeleton is designed to perform sitting to standing (STS) movements with a hybrid exoskeleton. A hierarchical control design is proposed to overcome the difficulties associated with developing an optimal real-time solution for the highly nonlinear and uncertain STS control model with multiple degrees of freedom. A higher-level robust nonlinear control design is derived to exponentially track a time-invariant desired STS movement profile. Then, a lower-level optimal control allocator is designed to distribute control between FES and the knee electric motors. The allocator uses a person's muscle fatigue and recovery dynamics to determine an optimal ratio between the FES-elicited knee torque and the exoskeleton assist. Experiments were performed on human participants, two persons without disability and one person with spinal cord injury (SCI), to validate the feedback controller and the optimal torque allocator. The muscles of the participant with SCI did not actively contract to FES, so he was only tested with the powered exoskeleton controller. The experimental results show that the proposed hierarchical control design is a promising method to effect shared control in a hybrid exoskeleton.